New Approaches for Removing the Effect of Water Damping on SMAP Freeze/Thaw Mapping

Abstract

The Northern Quebec landscape is typically covered by numerous lakes. The lowest emissivity of water bodies dominates the brightness temperature (Tb) data measured over this region. Thus, it is necessary to eliminate the effect of water bodies from Tb measurements. The primary objective of this study is to develop two approaches to correct the Soil Moisture Active Passive brightness temperature (SMAP L1C), collected between January and December of 2016, for the damping effect of water bodies within each 36 km by 36 km pixel. The first algorithm normalizes Tb with the intercept of its linear regression versus the water fraction of each pixel. A second algorithm used Tb regression with water fraction by vegetation classes for each scene. Surface soil temperature and moisture measured near Umiujaq were used to validate Tb correction. The proposed Tb corrections resolve the divergence observed with SMAP standard correction when the water fraction is higher than 20%. Corrected brightness temperature is then tested for mapping the soil freeze/thaw state using the Normalized Polarization Ratio. Agreements of up to 90% (ascending orbit) and 79% (descending orbit) were reached for the proposed approach versus 64% and 50% for the existing approach. R ESUM E Le paysage du Nord du Qu ebec comprend plusieurs lacs. La temp erature de brillance (Tb) mesur ee est domin ee par la plus basse emissivit e des surfaces d'eau. Ainsi, il est n ecessaire d' eliminer cet artifact. L'objectif principal de cette etude est de proposer deux nouvelles approches pour corriger la temp erature de brillance des produits SMAP L1C de l'effet att enuant des masses d'eau pours chacun des pixels de 36 km par 36 km d'images acquises entre janvier et d ecembre 2016. Le premier algorithme normalise les valeurs de Tb avec l'ordonn ee a l'origine de sa r egression lin eaire par rapport a la fraction de l'eau dans chacun des pixels. Le second algorithme normalise par rapport a la fraction de l'eau par classe de couverture v eg etale. Pour valider les valeurs corrig ees, nous avons utilis e des donn ees de temp erature et d'humidit e du sol de sondes install ees pr es d'Umiujaq. La correction propos ee de Tb r esout les divergences observ ees avec la correction SMAP de r ef erence lorsque la proportion d'eau au sein d'un pixel d epasse 20%. Le gel/non gel du sol a ensuite et e cartographi e en utilisant le Rapport de polarisation normalis e. Une concordance jusqu' a 90% (orbite ascendant) et 79% (orbite descendant) a et e obtenue par rapport a 64% et 50% pour l'approche de r ef erence.

Prospects for Detecting Volcanic Events with Microwave Radiometry

“…These data are available from 31 March 2015 to at least the date of this work's publication. The interpolation also takes into account the areal fraction of land or sea covered by each gridded element by mapping the 3 dB footprint center on a static high-resolution land/water mask (though other schemes have also been identified, e.g., Touati et al [16]). This increased fidelity is important for our application since many volcanoes are located near land/sea boundaries.…”

Landscape Freeze/Thaw Mapping from Active and Passive Microwave Earth Observations over the Tursujuq National Park, Quebec, Canada

“…Those SMAP data were in Level 1 C format (L1C), already geolocated, and calibrated from SMAP Level 1B (L1B). The brightness temperature values (Tb) extracted from SMAP L1C pixels were corrected from the damping effect of water as described by the normalization approach per vegetation type proposed by Touati et al (2019). Only 12 SMAP scenes acquired at the same timeline of ALOS PALSAR-2 overpasses (30 min earlier than SMAP scene) were analyzed for this study.…”

“…The adapted version of the F/T algorithm proposed by Touati et al (2019) was used to identify freezing or thawing soil states. The F/T algorithm is based on the Normalized Polarization Ratio (NPR) described by the following equation (Roy et al 2015;Rautiainen et al 2016):…”

“…As a result, they recommended that such pixels be removed. In the Touati et al (2019) study, we developed two approaches to correct SMAP L1C Tb products for the damping effect of water bodies in a given pixel. The first one, i.e., the normalization approach, normalizes Tb values with the intercept of its linear regression with the water fraction in a SMAP pixel.…”

“…In this study, we (1) investigate the sensitivity to vegetation cover type of active (PALSAR data) and passive (SMAP data) F/T classification, and (2) use F/T classification from high-resolution PALSAR data (30 m) to follow the evolution of frozen and thawed soil states determine by low-resolution SMAP data (36 km) using a version of the classification algorithm adapted by Touati et al (2019).…”